Federated split learning for sequential data in satellite–terrestrial integrated networks
W Jiang, H Han, Y Zhang, J Mu - Information Fusion, 2024 - Elsevier
Satellite–terrestrial integrated networks (STINs) have been proposed for B5G/6G mobile
communication, and the increase in the computation and communication capacities of …
communication, and the increase in the computation and communication capacities of …
On-board federated learning for satellite clusters with inter-satellite links
The emergence of mega-constellations of interconnected satellites has a major impact on
the integration of cellular wireless and non-terrestrial networks, while simultaneously …
the integration of cellular wireless and non-terrestrial networks, while simultaneously …
Communication-efficient federated learning for LEO satellite networks integrated with HAPs using hybrid NOMA-OFDM
Space AI has become increasingly important and sometimes even necessary for
government, businesses, and society. An active research topic under this mission is …
government, businesses, and society. An active research topic under this mission is …
Hyperdrive: scheduling serverless functions in the edge-cloud-space 3d continuum
The number of Low Earth Orbit (LEO) satellites has grown enormously in the past years.
Their abundance and low orbits allow for low latency communication with a satellite almost …
Their abundance and low orbits allow for low latency communication with a satellite almost …
Scheduling for On-Board Federated Learning with Satellite Clusters
Mega-constellations of small satellites have evolved into a source of massive amount of
valuable data. To manage this data efficiently, on-board federated learning (FL) enables …
valuable data. To manage this data efficiently, on-board federated learning (FL) enables …
Performance analysis of federated learning in orbital edge computing
Federated Learning (FL) is a promising solution for collaborative machine learning while
respecting data privacy and locality. FL has been used in Low Earth Orbit (LEO) satellite …
respecting data privacy and locality. FL has been used in Low Earth Orbit (LEO) satellite …
DFedSat: Communication-Efficient and Robust Decentralized Federated Learning for LEO Satellite Constellations
Low Earth Orbit (LEO) satellites play a crucial role in the development of 6G mobile networks
and space-air-ground integrated systems. Recent advancements in space technology have …
and space-air-ground integrated systems. Recent advancements in space technology have …
FedOrbit: Energy Efficient Federated Learning for Orbital Edge Computing Using Block Minifloat Arithmetic
Low Earth Orbit (LEO) satellite constellations have diverse applications, including earth
observation, communication services, navigation, and positioning. These constellations …
observation, communication services, navigation, and positioning. These constellations …
Stitching Satellites to the Edge: Pervasive and Efficient Federated LEO Satellite Learning
In the ambitious realm of space AI, the integration of federated learning (FL) with low Earth
orbit (LEO) satellite constellations holds immense promise. However, many challenges …
orbit (LEO) satellite constellations holds immense promise. However, many challenges …
Federated Deep Reinforcement Learning for Energy Efficient Multi-Functional RIS-Assisted Low-Earth Orbit Networks
In this paper, a novel network architecture that deploys the multi-functional reconfigurable
intelligent surface (MF-RIS) in low-Earth orbit (LEO) is proposed. Unlike traditional RIS with …
intelligent surface (MF-RIS) in low-Earth orbit (LEO) is proposed. Unlike traditional RIS with …